Curaçao Road Surface Classification from OpenStreetMap and Satellite Imagery

HeiGIT's dataset provides detailed road surface information for Curaçao, distinguishing paved from unpaved roads. The data originates from OpenStreetMap and is augmented with deep learning predictions based on Mapillary imagery and urban classification layers. It was last updated on March 2, 2026.

Use Cases

• Transportation planning based on road surface type and urban classification attributes.
• Infrastructure analysis based on OSM attributes like highway type, surface, and smoothness.
• Climate emissions assessment based on the proportion of paved versus unpaved roads.
• GIS applications requiring combined surface classifications from OSM and deep learning models.

Strengths

• Includes AI-derived surface classifications (paved/unpaved) from a hybrid deep learning approach.
• Combines multiple data sources: OpenStreetMap, Mapillary imagery, GHSU, and AFRICAPOLIS urban layers.
• Available in common geospatial formats: GEOJSON and GEOPACKAGE.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and dataset size are unknown, which may limit suitability assessment.

Provenance

Source

Heidelberg Institute for Geoinformation Technology (HeiGIT)

Collection Method

Derived from OpenStreetMap and augmented with deep learning predictions from Mapillary imagery.

Time Range

null

Freshness

Last updated 2026-03-02 17:24:38.144326; freshness should be verified.

Geography

Curaçao